Bidimensional Engineered Amorphous a-SnO2 Interfaces: Synthesis and Gas Sensing Response to H2S and Humidity

Two-dimensional (2D) transition metal dichalcogenides (TMDs) and metal chalcogenides (MCs), despite their excellent gas sensing properties, are subjected to spontaneous oxidation in ambient air, negatively affecting the sensor’s signal reproducibility in the long run. Taking advantage of spontaneous oxidation, we synthesized fully amorphous a-SnO2 2D flakes (≈30 nm thick) by annealing in air 2D SnSe2 for two weeks at temperatures below the crystallization temperature of SnO2 (T < 280 °C). These engineered a-SnO2 interfaces, preserving all the precursor’s 2D surface-to-volume features, are stable in dry/wet air up to 250 °C, with excellent baseline and sensor’s signal reproducibility to H2S (400 ppb to 1.5 ppm) and humidity (10–80% relative humidity (RH)) at 100 °C for one year. Specifically, by combined density functional theory and ab initio molecular dynamics, we demonstrated that H2S and H2O compete by dissociative chemisorption over the same a-SnO2 adsorption sites, disclosing the humidity cross-response to H2S sensing. Tests confirmed that humidity decreases the baseline resistance, hampers the H2S sensor’s signal (i.e., relative response (RR) = Ra/Rg), and increases the limit of detection (LOD). At 1 ppm, the H2S sensor’s signal decreases from an RR of 2.4 ± 0.1 at 0% RH to 1.9 ± 0.1 at 80% RH, while the LOD increases from 210 to 380 ppb. Utilizing a suitable thermal treatment, here, we report an amorphization procedure that can be easily extended to a large variety of TMDs and MCs, opening extraordinary applications for 2D layered amorphous metal oxide gas sensors.

Section S3 -Calculation of the low detection limit (LDL) and calibration lines to assess sensitivity Gas sensor sensitivity (SS) is represented by the slopes of the calibrating line lines obtained by plotting in a log-log scale (Rg/Ra)H2S as function of increasing H2S gas concentrations. According to the IUPAC definition 1s , the lowest detection limit (LDL) of a sensor can be estimated starting from experimental data, according to: where "slope" represents the slope of the linear fitting of the logarithm of relative response vs. the logarithm of the concentration. For the calculation of the rmsnoise, ten points at baseline (i.e. baseline (a) (b) before gas exposure) of the sensor were considered and fitted by a fifth order polynomial equation.
Then, rmsnoise was calculated as where N is the number of points, Ri are the experimental data points, and R is the calculated value from the fifth order polynomial fitting.
In our case, for H2S, the noise and slope values of the sensor were 0.04 and 0.55 ppm -1 respectively, giving an LDL value of the H2S sensor of about 0.21 ± 0.1 ppm.

Computational procedure & validation of the model
The modeling of the amorphous a-SnO2 NS ( Figure S8) has been inspired by that of amorphous TiO2 ones, 2s,3s while the anchoring mechanisms of H2S molecule stem from a chemisorbed and physisorbed (molecular) model, related to H2S adsorption on stable crystalline rutile SnO2 surfaces. 4s Specifically, we considered 4 initial guesses, i.e. chemisorbed H2S (with one broken H-S bond) on top of: (i) a 4-fold and (ii) a 5-fold Sn at the surface of a-SnO2 NS and physisorbed H2S still on top of a (iii) 4-fold and a (iv) 5-fold Sn at the surface of a-SnO2 NS. The overall physisorption and chemisorption attack mechanisms are sketched in Figure S8a  Corresponding H2S molecule's adsorption energies (Eads) on the amorphous surface has been computed according to the following equation: where Esurf_H2S, Esurf, and E H2S are the energy of the final system with the hydrogen sulfide molecule anchored on the a-SnO2 NS surface, of a single optimized molecule of H2S, and of the optimized initial clean a-SnO2 NS respectively. Remarkably, the adsorption energies calculated with Eq. (S1) for (i-iv) H2S anchoring are all quantitatively endothermic (i.e. Eads > 0) with the molecularly adsorbed ones ( Figure S8a) more unstable than the chemisorbed systems ( Figure S8b), partly supporting previously reported data for H2S adsorbed on SnO2 rutile (110) surface. 4s Such unexpected result was further investigated considering the occurrence of other different geometries obtained by thermalizing the initially calculated (i-iv) metastable systems at 300 K, by means of short AIMD runs and subsequently re-optimizing some representative trajectories for each system at the DFT level (0 K, PAW/PBE). Following this procedure, we found three exothermic geometries, all chemisorbed, whose structural features are discussed in the main text. Accordingly, adsorption energies (Eads) shown in Table 3 refer to (i) values obtained by thermalizing (300 K, AIMD) and re-optimizing (0 K, DFT) only products (i.e., precisely the term Esurf _H2S only in Eq.(S1)), (ii) values (in brackets) obtained by thermalizing (300 K, AIMD) and re-optimizing (0 K, DFT) for the sake of consistency both products and reactants of the anchoring (i.e., both Esurf _H2S and Esurf terms in Eq.(S1)). Notably, Eads values, despite being smaller for the latter case, show a consistent trend (exothermic), attesting no significant changes in the adsorption thermodynamics (i.e., by thermalizing or not the clean a-SnO2 at 300 K before the DFT optimization), a result that in this case can be ascribed to a temperature-driven saturation of dangling bonds initially present in the amorphous layers.
As for the case of H2S, in this study we additionally thermalized water chemisorbed structure with short AIMD runs at 300 K, further re-optimizing at DFT level some trajectories of relevance, yielding no significant structural differences by comparing the combined AIMD+DFT computations with previous DFT ones 5s .

Theoretical setup
Geometry optimization of the free-standing amorphous layer of SnO2 and of the H2S//a-SnO2 anchored systems was performed by means of Density Functional Theory (DFT)-based simulations as implemented in the Vienna Ab-initio Simulation Package (VASP) code. 6s-9s We similarly employed the projector augmented wave (PAW) method 10s along with the generalized gradient approximation exchange-correlation functional as parametrized by Perdew-Burke-Ernzerhof (PBE). 11s The DFT-D3 dispersion correction was also used to include the van der Waals interactions 12s , 13s . We selected plane-wave cutoff energy of 600 eV. All the structures were optimized until the forces on all atoms were smaller than 0.04 eV/Å.
Starting from the initially optimized structure of bulk a-SnO2 (192 atoms, 64 Sn, 128 O, 3 × 3 × 3 Γcentered k-point sampling of the Brillouin Zone (see ref. [5s] for further details) we have added a large amount of vacuum (~15 Å) along the three directions to assemble the nanosheets (NSs) and prevent accordingly spurious interactions among the replicas in the non-periodic directions. We corrected all the slabs for the possible residual dipole still along the non-periodic directions and fully re-optimized both lattice parameters and ionic positions in all the systems investigated, finding that the most stable orientation is the one where the non-periodic direction is oriented along the c-axis (see Figure S9). NS in-plane optimized lattice parameters are a = 13.17 and b = 13.37 Å, respectively.
The initial anchoring systems reported in the sketch in Figure S8 are thus optimized at the PAW/PBE level of theory. As mentioned, the initially obtained i-iv systems (described in the main text) are all endothermic.

Ab-Initio Molecular Dynamics (AIMD) simulations 14s have been accordingly performed to better
shed light on the anchoring mechanism. In particular, short runs of 5 ps (2.5 ps for equilibration, 2.5 ps for production) have been performed on the initially DFT optimized anchoring geometries in a canonical ensamble (NVT) at T = 300 K and with a timestep of 0.5 fs. 14s A significant trajectory after 5 ps is thus extracted for each anchored system which is once more fully re-optimized @PAW/PBE.

Synthesis of amorphous a-SnO2
SnSe2 crystals (Ossila -UK) were exfoliated in NMP (N-Methyl-2-pyrrolidone, Sigma-Aldrich) solvent by means of Sonication-Assisted Liquid Phase Exfoliation (LPE). The dispersion was sonicated at 25 °C using a Sonics VC 505 working at 20 kHz and 400 W for 3 hours and subsequently centrifuged to remove the solvent.
Flakes were then redispersed in ethanol, spin-coated over Si3N4 (at 1500 rpm for 30 s) substrates, and successively annealed in static air at 250 °C for two weeks.

Materials characterization
Microstructure was investigated by SEM imaging (Gemini FESEM 500) working at an accelerating voltage of 2 kV, and by TEM, HRTEM and SAED performed using Jeol JEM 2010F (Jeol Ltd., Tokyo, Japan) operating at 200 kV. Thermogravimetric (TG) and differential thermal (DTA) analyses of exfoliated SnSe2 were carried out in air in Air and in N2 atmospheres using LINSEIS L81-I at a heating rate at 5 °C/min from 25 °C to 1050 °C. XPS spectra were collected using a PHI 1257 spectrometer equipped with monochromatic Al Kα source (hν = 1486.6 eV) and operating at a spectral resolution of 250 meV. Grazing Incidence X-Ray Diffraction (GIXRD) was performed by XRD-PAN Analytical X'PERT Pro using Cu Kα1 radiation (λ = 1.5406 Å) in parallel geometry using an incident angle of 0.8°.

Gas sensing measurements
Thin films were prepared by spin coating 50 μL of centrifuged dispersion containing 2D SnSe2 nanosheets over Si3N4 substrates provided with Pt finger type electrodes (30 micron apart) on front side and heater on backside and mounted inside a Teflon test chamber (500 cm 3 ) to measure resistance variations (Agilent 34970A). Thin films were in situ annealed at 250 °C in dry air for two weeks to yield amorphous a-SnO2, while in "operando" monitoring the variation of the baseline resistance as previously reported 28 . After baseline resistance stabilization, films were exposed to H2S and humidity at different concentrations in the temperature range 25-150 °C. Different H2S concentrations in the range 400 ppb -1.5 ppm were obtained by diluting in dry air certified H2S gas mixture (5 ppm in air) using mass flow controllers (MKS 147) with a constant flow rate of 500 sccm/min. Distinct relative humidity's (RH%) were obtained by mixing dry air with saturated water vapor air and RH% content monitored before injection at a temperature of 25 °C (Thermo-Hygrometer AHTD-625). The following definitions were applied in gas sensing measurements: (BLR), Baseline Resistance represented by the sensor's electrical resistance in air at equilibrium; sensor's signal or Relative Response, the relative resistances changes RR = RAir/RGas for a given concentration of gases; (S), Sensor Sensitivity, the slope of the calibration curve in the log-log sensitivity plot; (ADS, DES) adsorption and desorption times, the time needed to reach 90% of the resistance value at equilibrium after adsorption and desorption of the analyte.